{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "sublime-making",
   "metadata": {},
   "source": [
    "## 数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "atomic-africa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "confirmed-console",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4'13</td>\n",
       "      <td>8.88</td>\n",
       "      <td>195.0</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2785</td>\n",
       "      <td>170.0</td>\n",
       "      <td>72.6</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4'16</td>\n",
       "      <td>7.70</td>\n",
       "      <td>225.0</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>3133</td>\n",
       "      <td>174.0</td>\n",
       "      <td>52.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4'09</td>\n",
       "      <td>8.45</td>\n",
       "      <td>218.0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>3901</td>\n",
       "      <td>169.0</td>\n",
       "      <td>46.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4'21</td>\n",
       "      <td>8.05</td>\n",
       "      <td>206.0</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>4946</td>\n",
       "      <td>183.0</td>\n",
       "      <td>79.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3'44</td>\n",
       "      <td>7.52</td>\n",
       "      <td>210.0</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>3538</td>\n",
       "      <td>171.0</td>\n",
       "      <td>54.7</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4'23</td>\n",
       "      <td>8.27</td>\n",
       "      <td>208.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4647</td>\n",
       "      <td>176.0</td>\n",
       "      <td>69.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>5'19</td>\n",
       "      <td>9.55</td>\n",
       "      <td>210.0</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>7042</td>\n",
       "      <td>177.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>3'25</td>\n",
       "      <td>7.50</td>\n",
       "      <td>252.0</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>5755</td>\n",
       "      <td>181.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4'39</td>\n",
       "      <td>7.81</td>\n",
       "      <td>208.0</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>5688</td>\n",
       "      <td>172.0</td>\n",
       "      <td>51.7</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>477 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别 男1000米跑  男50米跑    男跳远  男体前屈  男引体  男肺活量     身高    体重  BMI\n",
       "0     1  男    4'13   8.88  195.0    12    1  2785  170.0  72.6    0\n",
       "1     1  男    4'16   7.70  225.0    11    7  3133  174.0  52.7    0\n",
       "2     1  男    4'09   8.45  218.0    14    1  3901  169.0  46.5    0\n",
       "3     1  男    4'21   8.05  206.0    13    1  4946  183.0  79.7    0\n",
       "4     1  男    3'44   7.52  210.0    13    9  3538  171.0  54.7    0\n",
       "..   .. ..     ...    ...    ...   ...  ...   ...    ...   ...  ...\n",
       "472  17  男    4'23   8.27  208.0    10    0  4647  176.0  69.5    0\n",
       "473  17  男    5'19   9.55  210.0    15    6  7042  177.0  76.0    0\n",
       "474  17  男    3'25   7.50  252.0    13   13  5755  181.0  65.0    0\n",
       "475  17  男    4'39   7.81  208.0    14   11  5688  172.0  51.7    0\n",
       "476  17  男       0   0.00    0.0     0    0     0    0.0   0.0    0\n",
       "\n",
       "[477 rows x 11 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 男生\n",
    "score_m = pd.read_excel('./18级高一体测成绩汇总.xls')\n",
    "score_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "confirmed-lodging",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>班级</th>\n",
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       "      <th>女800米跑</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女肺活量</th>\n",
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       "      <td>女</td>\n",
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       "      <td>3683</td>\n",
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       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
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       "      <td>3331</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>9.52</td>\n",
       "      <td>172.0</td>\n",
       "      <td>21</td>\n",
       "      <td>46</td>\n",
       "      <td>3701</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.7</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>9.79</td>\n",
       "      <td>145.0</td>\n",
       "      <td>8</td>\n",
       "      <td>34</td>\n",
       "      <td>3592</td>\n",
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       "      <td>63.9</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>588</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.51</td>\n",
       "      <td>9.60</td>\n",
       "      <td>150.0</td>\n",
       "      <td>24</td>\n",
       "      <td>41</td>\n",
       "      <td>2255</td>\n",
       "      <td>158.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>589</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.00</td>\n",
       "      <td>10.18</td>\n",
       "      <td>150.0</td>\n",
       "      <td>13</td>\n",
       "      <td>36</td>\n",
       "      <td>2937</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.7</td>\n",
       "      <td>0</td>\n",
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       "      <th>590</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.45</td>\n",
       "      <td>10.18</td>\n",
       "      <td>152.0</td>\n",
       "      <td>15</td>\n",
       "      <td>35</td>\n",
       "      <td>2592</td>\n",
       "      <td>165.0</td>\n",
       "      <td>48.6</td>\n",
       "      <td>0</td>\n",
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       "      <th>591</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.01</td>\n",
       "      <td>9.67</td>\n",
       "      <td>165.0</td>\n",
       "      <td>10</td>\n",
       "      <td>41</td>\n",
       "      <td>1829</td>\n",
       "      <td>154.0</td>\n",
       "      <td>43.6</td>\n",
       "      <td>0</td>\n",
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       "      <th>592</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.48</td>\n",
       "      <td>9.09</td>\n",
       "      <td>180.0</td>\n",
       "      <td>10</td>\n",
       "      <td>46</td>\n",
       "      <td>2962</td>\n",
       "      <td>162.0</td>\n",
       "      <td>55.3</td>\n",
       "      <td>0</td>\n",
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       "<p>593 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别  女800米跑  女50米跑    女跳远  女体前屈  女仰卧  女肺活量     身高    体重  BMI\n",
       "0     1  女    3.22   9.32  185.0    16   48  3775  163.0  51.3    0\n",
       "1     1  女    4.59  11.44  148.0     9   29  3683  163.0  66.6    0\n",
       "2     1  女    3.46  13.40  150.0     7   40  3331  157.0  60.0    0\n",
       "3     1  女    3.39   9.52  172.0    21   46  3701  160.0  50.7    0\n",
       "4     1  女    3.43   9.79  145.0     8   34  3592  167.0  63.9    0\n",
       "..   .. ..     ...    ...    ...   ...  ...   ...    ...   ...  ...\n",
       "588  17  女    3.51   9.60  150.0    24   41  2255  158.0  49.0    0\n",
       "589  17  女    4.00  10.18  150.0    13   36  2937  161.0  55.7    0\n",
       "590  17  女    3.45  10.18  152.0    15   35  2592  165.0  48.6    0\n",
       "591  17  女    4.01   9.67  165.0    10   41  1829  154.0  43.6    0\n",
       "592  17  女    4.48   9.09  180.0    10   46  2962  162.0  55.3    0\n",
       "\n",
       "[593 rows x 11 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 女生\n",
    "score_f = pd.read_excel('./18级高一体测成绩汇总.xls',sheet_name=1)\n",
    "score_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "legislative-frost",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th colspan=\"2\" halign=\"left\">男50米跑</th>\n",
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       "      <th></th>\n",
       "      <th>成绩</th>\n",
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       "      <th>成绩</th>\n",
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       "      <td>100</td>\n",
       "      <td>53</td>\n",
       "      <td>100</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>100</td>\n",
       "      <td>3'24\"</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4420</td>\n",
       "      <td>95</td>\n",
       "      <td>3100</td>\n",
       "      <td>95</td>\n",
       "      <td>7.2</td>\n",
       "      <td>95</td>\n",
       "      <td>7.9</td>\n",
       "      <td>95</td>\n",
       "      <td>21.5</td>\n",
       "      <td>95</td>\n",
       "      <td>...</td>\n",
       "      <td>198</td>\n",
       "      <td>95</td>\n",
       "      <td>15.0</td>\n",
       "      <td>95</td>\n",
       "      <td>51</td>\n",
       "      <td>95</td>\n",
       "      <td>3'35\"</td>\n",
       "      <td>95</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4300</td>\n",
       "      <td>90</td>\n",
       "      <td>3050</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>90</td>\n",
       "      <td>8.0</td>\n",
       "      <td>90</td>\n",
       "      <td>19.4</td>\n",
       "      <td>90</td>\n",
       "      <td>...</td>\n",
       "      <td>192</td>\n",
       "      <td>90</td>\n",
       "      <td>14.0</td>\n",
       "      <td>90</td>\n",
       "      <td>49</td>\n",
       "      <td>90</td>\n",
       "      <td>3'40\"</td>\n",
       "      <td>90</td>\n",
       "      <td>3'36\"</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4050</td>\n",
       "      <td>85</td>\n",
       "      <td>2900</td>\n",
       "      <td>85</td>\n",
       "      <td>7.4</td>\n",
       "      <td>85</td>\n",
       "      <td>8.3</td>\n",
       "      <td>85</td>\n",
       "      <td>17.2</td>\n",
       "      <td>85</td>\n",
       "      <td>...</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>13.0</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3'47\"</td>\n",
       "      <td>85</td>\n",
       "      <td>3'43\"</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3800</td>\n",
       "      <td>80</td>\n",
       "      <td>2750</td>\n",
       "      <td>80</td>\n",
       "      <td>7.5</td>\n",
       "      <td>80</td>\n",
       "      <td>8.6</td>\n",
       "      <td>80</td>\n",
       "      <td>15.0</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>178</td>\n",
       "      <td>80</td>\n",
       "      <td>12.0</td>\n",
       "      <td>80</td>\n",
       "      <td>43</td>\n",
       "      <td>80</td>\n",
       "      <td>3'55\"</td>\n",
       "      <td>80</td>\n",
       "      <td>3'50\"</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3680</td>\n",
       "      <td>78</td>\n",
       "      <td>2650</td>\n",
       "      <td>78</td>\n",
       "      <td>7.7</td>\n",
       "      <td>78</td>\n",
       "      <td>8.8</td>\n",
       "      <td>78</td>\n",
       "      <td>13.6</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>175</td>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>4'00\"</td>\n",
       "      <td>78</td>\n",
       "      <td>3'55\"</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3560</td>\n",
       "      <td>76</td>\n",
       "      <td>2550</td>\n",
       "      <td>76</td>\n",
       "      <td>7.9</td>\n",
       "      <td>76</td>\n",
       "      <td>9.0</td>\n",
       "      <td>76</td>\n",
       "      <td>12.2</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>11.0</td>\n",
       "      <td>76</td>\n",
       "      <td>39</td>\n",
       "      <td>76</td>\n",
       "      <td>4'05\"</td>\n",
       "      <td>76</td>\n",
       "      <td>4'00\"</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3440</td>\n",
       "      <td>74</td>\n",
       "      <td>2450</td>\n",
       "      <td>74</td>\n",
       "      <td>8.1</td>\n",
       "      <td>74</td>\n",
       "      <td>9.2</td>\n",
       "      <td>74</td>\n",
       "      <td>10.8</td>\n",
       "      <td>74</td>\n",
       "      <td>...</td>\n",
       "      <td>169</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74</td>\n",
       "      <td>37</td>\n",
       "      <td>74</td>\n",
       "      <td>4'10\"</td>\n",
       "      <td>74</td>\n",
       "      <td>4'05\"</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3320</td>\n",
       "      <td>72</td>\n",
       "      <td>2350</td>\n",
       "      <td>72</td>\n",
       "      <td>8.3</td>\n",
       "      <td>72</td>\n",
       "      <td>9.4</td>\n",
       "      <td>72</td>\n",
       "      <td>9.4</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>166</td>\n",
       "      <td>72</td>\n",
       "      <td>10.0</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>4'15\"</td>\n",
       "      <td>72</td>\n",
       "      <td>4'10\"</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3200</td>\n",
       "      <td>70</td>\n",
       "      <td>2250</td>\n",
       "      <td>70</td>\n",
       "      <td>8.5</td>\n",
       "      <td>70</td>\n",
       "      <td>9.6</td>\n",
       "      <td>70</td>\n",
       "      <td>8.0</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>163</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70</td>\n",
       "      <td>33</td>\n",
       "      <td>70</td>\n",
       "      <td>4'20\"</td>\n",
       "      <td>70</td>\n",
       "      <td>4'15\"</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3080</td>\n",
       "      <td>68</td>\n",
       "      <td>2150</td>\n",
       "      <td>68</td>\n",
       "      <td>8.7</td>\n",
       "      <td>68</td>\n",
       "      <td>9.8</td>\n",
       "      <td>68</td>\n",
       "      <td>6.6</td>\n",
       "      <td>68</td>\n",
       "      <td>...</td>\n",
       "      <td>160</td>\n",
       "      <td>68</td>\n",
       "      <td>9.0</td>\n",
       "      <td>68</td>\n",
       "      <td>31</td>\n",
       "      <td>68</td>\n",
       "      <td>4'25\"</td>\n",
       "      <td>68</td>\n",
       "      <td>4'20\"</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2960</td>\n",
       "      <td>66</td>\n",
       "      <td>2050</td>\n",
       "      <td>66</td>\n",
       "      <td>8.9</td>\n",
       "      <td>66</td>\n",
       "      <td>10.0</td>\n",
       "      <td>66</td>\n",
       "      <td>5.2</td>\n",
       "      <td>66</td>\n",
       "      <td>...</td>\n",
       "      <td>157</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>4'30\"</td>\n",
       "      <td>66</td>\n",
       "      <td>4'25\"</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2840</td>\n",
       "      <td>64</td>\n",
       "      <td>1950</td>\n",
       "      <td>64</td>\n",
       "      <td>9.1</td>\n",
       "      <td>64</td>\n",
       "      <td>10.2</td>\n",
       "      <td>64</td>\n",
       "      <td>3.8</td>\n",
       "      <td>64</td>\n",
       "      <td>...</td>\n",
       "      <td>154</td>\n",
       "      <td>64</td>\n",
       "      <td>8.0</td>\n",
       "      <td>64</td>\n",
       "      <td>27</td>\n",
       "      <td>64</td>\n",
       "      <td>4'35\"</td>\n",
       "      <td>64</td>\n",
       "      <td>4'30\"</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2720</td>\n",
       "      <td>62</td>\n",
       "      <td>1850</td>\n",
       "      <td>62</td>\n",
       "      <td>9.3</td>\n",
       "      <td>62</td>\n",
       "      <td>10.4</td>\n",
       "      <td>62</td>\n",
       "      <td>2.4</td>\n",
       "      <td>62</td>\n",
       "      <td>...</td>\n",
       "      <td>151</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62</td>\n",
       "      <td>25</td>\n",
       "      <td>62</td>\n",
       "      <td>4'40\"</td>\n",
       "      <td>62</td>\n",
       "      <td>4'35\"</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2600</td>\n",
       "      <td>60</td>\n",
       "      <td>1750</td>\n",
       "      <td>60</td>\n",
       "      <td>9.5</td>\n",
       "      <td>60</td>\n",
       "      <td>10.6</td>\n",
       "      <td>60</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60</td>\n",
       "      <td>...</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>7.0</td>\n",
       "      <td>60</td>\n",
       "      <td>23</td>\n",
       "      <td>60</td>\n",
       "      <td>4'45\"</td>\n",
       "      <td>60</td>\n",
       "      <td>4'40\"</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2470</td>\n",
       "      <td>50</td>\n",
       "      <td>1710</td>\n",
       "      <td>50</td>\n",
       "      <td>9.7</td>\n",
       "      <td>50</td>\n",
       "      <td>10.8</td>\n",
       "      <td>50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>143</td>\n",
       "      <td>50</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50</td>\n",
       "      <td>21</td>\n",
       "      <td>50</td>\n",
       "      <td>5'05\"</td>\n",
       "      <td>50</td>\n",
       "      <td>4'50\"</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2340</td>\n",
       "      <td>40</td>\n",
       "      <td>1670</td>\n",
       "      <td>40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>40</td>\n",
       "      <td>11.0</td>\n",
       "      <td>40</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>40</td>\n",
       "      <td>...</td>\n",
       "      <td>138</td>\n",
       "      <td>40</td>\n",
       "      <td>5.0</td>\n",
       "      <td>40</td>\n",
       "      <td>19</td>\n",
       "      <td>40</td>\n",
       "      <td>5'25\"</td>\n",
       "      <td>40</td>\n",
       "      <td>5'00\"</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2210</td>\n",
       "      <td>30</td>\n",
       "      <td>1630</td>\n",
       "      <td>30</td>\n",
       "      <td>10.1</td>\n",
       "      <td>30</td>\n",
       "      <td>11.2</td>\n",
       "      <td>30</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>133</td>\n",
       "      <td>30</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>5'45\"</td>\n",
       "      <td>30</td>\n",
       "      <td>5'10\"</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2080</td>\n",
       "      <td>20</td>\n",
       "      <td>1590</td>\n",
       "      <td>20</td>\n",
       "      <td>10.3</td>\n",
       "      <td>20</td>\n",
       "      <td>11.4</td>\n",
       "      <td>20</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>20</td>\n",
       "      <td>...</td>\n",
       "      <td>128</td>\n",
       "      <td>20</td>\n",
       "      <td>3.0</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>6'05\"</td>\n",
       "      <td>20</td>\n",
       "      <td>5'20\"</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1950</td>\n",
       "      <td>10</td>\n",
       "      <td>1550</td>\n",
       "      <td>10</td>\n",
       "      <td>10.5</td>\n",
       "      <td>10</td>\n",
       "      <td>11.6</td>\n",
       "      <td>10</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>123</td>\n",
       "      <td>10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>6'25\"</td>\n",
       "      <td>10</td>\n",
       "      <td>5'30\"</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    男肺活量       女肺活量      男50米跑      女50米跑       男体前屈       ...  女跳远       \\\n",
       "      成绩   分数    成绩   分数    成绩   分数    成绩   分数    成绩   分数  ...   成绩   分数   \n",
       "0   4540  100  3150  100   7.1  100   7.8  100  23.6  100  ...  204  100   \n",
       "1   4420   95  3100   95   7.2   95   7.9   95  21.5   95  ...  198   95   \n",
       "2   4300   90  3050   90   7.3   90   8.0   90  19.4   90  ...  192   90   \n",
       "3   4050   85  2900   85   7.4   85   8.3   85  17.2   85  ...  185   85   \n",
       "4   3800   80  2750   80   7.5   80   8.6   80  15.0   80  ...  178   80   \n",
       "5   3680   78  2650   78   7.7   78   8.8   78  13.6   78  ...  175   78   \n",
       "6   3560   76  2550   76   7.9   76   9.0   76  12.2   76  ...  172   76   \n",
       "7   3440   74  2450   74   8.1   74   9.2   74  10.8   74  ...  169   74   \n",
       "8   3320   72  2350   72   8.3   72   9.4   72   9.4   72  ...  166   72   \n",
       "9   3200   70  2250   70   8.5   70   9.6   70   8.0   70  ...  163   70   \n",
       "10  3080   68  2150   68   8.7   68   9.8   68   6.6   68  ...  160   68   \n",
       "11  2960   66  2050   66   8.9   66  10.0   66   5.2   66  ...  157   66   \n",
       "12  2840   64  1950   64   9.1   64  10.2   64   3.8   64  ...  154   64   \n",
       "13  2720   62  1850   62   9.3   62  10.4   62   2.4   62  ...  151   62   \n",
       "14  2600   60  1750   60   9.5   60  10.6   60   1.0   60  ...  148   60   \n",
       "15  2470   50  1710   50   9.7   50  10.8   50   0.0   50  ...  143   50   \n",
       "16  2340   40  1670   40   9.9   40  11.0   40  -1.0   40  ...  138   40   \n",
       "17  2210   30  1630   30  10.1   30  11.2   30  -2.0   30  ...  133   30   \n",
       "18  2080   20  1590   20  10.3   20  11.4   20  -3.0   20  ...  128   20   \n",
       "19  1950   10  1550   10  10.5   10  11.6   10  -4.0   10  ...  123   10   \n",
       "\n",
       "     男引体      女仰卧      男1000米跑      女800米跑       \n",
       "      成绩   分数  成绩   分数      成绩   分数     成绩   分数  \n",
       "0   16.0  100  53  100   3'30\"  100  3'24\"  100  \n",
       "1   15.0   95  51   95   3'35\"   95  3'30\"   95  \n",
       "2   14.0   90  49   90   3'40\"   90  3'36\"   90  \n",
       "3   13.0   85  46   85   3'47\"   85  3'43\"   85  \n",
       "4   12.0   80  43   80   3'55\"   80  3'50\"   80  \n",
       "5    NaN   78  41   78   4'00\"   78  3'55\"   78  \n",
       "6   11.0   76  39   76   4'05\"   76  4'00\"   76  \n",
       "7    NaN   74  37   74   4'10\"   74  4'05\"   74  \n",
       "8   10.0   72  35   72   4'15\"   72  4'10\"   72  \n",
       "9    NaN   70  33   70   4'20\"   70  4'15\"   70  \n",
       "10   9.0   68  31   68   4'25\"   68  4'20\"   68  \n",
       "11   NaN   66  29   66   4'30\"   66  4'25\"   66  \n",
       "12   8.0   64  27   64   4'35\"   64  4'30\"   64  \n",
       "13   NaN   62  25   62   4'40\"   62  4'35\"   62  \n",
       "14   7.0   60  23   60   4'45\"   60  4'40\"   60  \n",
       "15   6.0   50  21   50   5'05\"   50  4'50\"   50  \n",
       "16   5.0   40  19   40   5'25\"   40  5'00\"   40  \n",
       "17   4.0   30  17   30   5'45\"   30  5'10\"   30  \n",
       "18   3.0   20  15   20   6'05\"   20  5'20\"   20  \n",
       "19   2.0   10  13   10   6'25\"   10  5'30\"   10  \n",
       "\n",
       "[20 rows x 24 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 评分标准加载\n",
    "mark_sheet =  pd.read_excel('./体侧成绩评分表.xls',header = [0,1])\n",
    "mark_sheet"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "permanent-stone",
   "metadata": {},
   "source": [
    "## 数据类型转换"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "expired-mumbai",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 数据类型转换：男1000米跑"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "steady-poverty",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>minutes</th>\n",
       "      <th>seconds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
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       "      <td>4</td>\n",
       "      <td>16</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>472</th>\n",
       "      <td>4</td>\n",
       "      <td>23</td>\n",
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       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>4</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>477 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    minutes seconds\n",
       "0         4      13\n",
       "1         4      16\n",
       "2         4      09\n",
       "3         4      21\n",
       "4         3      44\n",
       "..      ...     ...\n",
       "472       4      23\n",
       "473       5      19\n",
       "474       3      25\n",
       "475       4      39\n",
       "476     NaN     NaN\n",
       "\n",
       "[477 rows x 2 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fuzhu = score_m['男1000米跑'].str.extract(r\"(\\d+)'(\\d+)\").rename(columns={0:'minutes',1:'seconds'})\n",
    "fuzhu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "finished-tackle",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 477 entries, 0 to 476\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   minutes  451 non-null    float64\n",
      " 1   seconds  451 non-null    float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 7.6 KB\n"
     ]
    }
   ],
   "source": [
    "fuzhu['minutes']=pd.to_numeric(fuzhu['minutes'])\n",
    "fuzhu['seconds']=pd.to_numeric(fuzhu['seconds'])\n",
    "fuzhu.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "developing-powell",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男肺活量</th>\n",
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       "      <th>BMI</th>\n",
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       "  <tbody>\n",
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       "      <td>8.88</td>\n",
       "      <td>195.0</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2785</td>\n",
       "      <td>170.0</td>\n",
       "      <td>72.6</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>4'16</td>\n",
       "      <td>7.70</td>\n",
       "      <td>225.0</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>3133</td>\n",
       "      <td>174.0</td>\n",
       "      <td>52.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
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       "      <td>4'09</td>\n",
       "      <td>8.45</td>\n",
       "      <td>218.0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>3901</td>\n",
       "      <td>169.0</td>\n",
       "      <td>46.5</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4'21</td>\n",
       "      <td>8.05</td>\n",
       "      <td>206.0</td>\n",
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       "      <td>4946</td>\n",
       "      <td>183.0</td>\n",
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       "    <tr>\n",
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       "      <td>3'44</td>\n",
       "      <td>7.52</td>\n",
       "      <td>210.0</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>3538</td>\n",
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       "      <th>472</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4'23</td>\n",
       "      <td>8.27</td>\n",
       "      <td>208.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4647</td>\n",
       "      <td>176.0</td>\n",
       "      <td>69.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>5'19</td>\n",
       "      <td>9.55</td>\n",
       "      <td>210.0</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>7042</td>\n",
       "      <td>177.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>3'25</td>\n",
       "      <td>7.50</td>\n",
       "      <td>252.0</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>5755</td>\n",
       "      <td>181.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4'39</td>\n",
       "      <td>7.81</td>\n",
       "      <td>208.0</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>5688</td>\n",
       "      <td>172.0</td>\n",
       "      <td>51.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "</table>\n",
       "<p>477 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别 男1000米跑  男50米跑    男跳远  男体前屈  男引体  男肺活量     身高    体重  BMI\n",
       "0     1  男    4'13   8.88  195.0    12    1  2785  170.0  72.6    0\n",
       "1     1  男    4'16   7.70  225.0    11    7  3133  174.0  52.7    0\n",
       "2     1  男    4'09   8.45  218.0    14    1  3901  169.0  46.5    0\n",
       "3     1  男    4'21   8.05  206.0    13    1  4946  183.0  79.7    0\n",
       "4     1  男    3'44   7.52  210.0    13    9  3538  171.0  54.7    0\n",
       "..   .. ..     ...    ...    ...   ...  ...   ...    ...   ...  ...\n",
       "472  17  男    4'23   8.27  208.0    10    0  4647  176.0  69.5    0\n",
       "473  17  男    5'19   9.55  210.0    15    6  7042  177.0  76.0    0\n",
       "474  17  男    3'25   7.50  252.0    13   13  5755  181.0  65.0    0\n",
       "475  17  男    4'39   7.81  208.0    14   11  5688  172.0  51.7    0\n",
       "476  17  男       0   0.00    0.0     0    0     0    0.0   0.0    0\n",
       "\n",
       "[477 rows x 11 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "difficult-infrared",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 477 entries, 0 to 476\n",
      "Data columns (total 11 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   班级       477 non-null    int64  \n",
      " 1   性别       477 non-null    object \n",
      " 2   男1000米跑  451 non-null    float64\n",
      " 3   男50米跑    477 non-null    float64\n",
      " 4   男跳远      477 non-null    float64\n",
      " 5   男体前屈     477 non-null    int64  \n",
      " 6   男引体      477 non-null    int64  \n",
      " 7   男肺活量     477 non-null    int64  \n",
      " 8   身高       477 non-null    float64\n",
      " 9   体重       477 non-null    float64\n",
      " 10  BMI      477 non-null    int64  \n",
      "dtypes: float64(5), int64(5), object(1)\n",
      "memory usage: 41.1+ KB\n"
     ]
    }
   ],
   "source": [
    "score_m['男1000米跑'] = (fuzhu['minutes']+fuzhu['seconds']/60).round(1)\n",
    "score_m.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "manual-oliver",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 男1000米跑和女800米跑"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "characteristic-sellers",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>女50米跑</th>\n",
       "      <th>女800米跑</th>\n",
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       "      <td>95.0</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.0</td>\n",
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       "      <td>95</td>\n",
       "      <td>95</td>\n",
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       "      <td>90</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>85.0</td>\n",
       "      <td>85</td>\n",
       "      <td>85</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85</td>\n",
       "      <td>85</td>\n",
       "      <td>85</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80.0</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>78.0</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>76.0</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>76.0</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>76.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>74.0</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>74.0</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>74.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>72.0</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>70.0</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>68.0</td>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>68.0</td>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>68.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>66.0</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66.0</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>64.0</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>60.0</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>30.0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">成绩</th>\n",
       "      <th>0</th>\n",
       "      <td>7.8</td>\n",
       "      <td>3'24\"</td>\n",
       "      <td>53</td>\n",
       "      <td>24.2</td>\n",
       "      <td>3150</td>\n",
       "      <td>204</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>7.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4540</td>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.9</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>51</td>\n",
       "      <td>22.5</td>\n",
       "      <td>3100</td>\n",
       "      <td>198</td>\n",
       "      <td>3'35\"</td>\n",
       "      <td>7.2</td>\n",
       "      <td>21.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4420</td>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.0</td>\n",
       "      <td>3'36\"</td>\n",
       "      <td>49</td>\n",
       "      <td>20.8</td>\n",
       "      <td>3050</td>\n",
       "      <td>192</td>\n",
       "      <td>3'40\"</td>\n",
       "      <td>7.3</td>\n",
       "      <td>19.4</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4300</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.3</td>\n",
       "      <td>3'43\"</td>\n",
       "      <td>46</td>\n",
       "      <td>19.1</td>\n",
       "      <td>2900</td>\n",
       "      <td>185</td>\n",
       "      <td>3'47\"</td>\n",
       "      <td>7.4</td>\n",
       "      <td>17.2</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4050</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.6</td>\n",
       "      <td>3'50\"</td>\n",
       "      <td>43</td>\n",
       "      <td>17.4</td>\n",
       "      <td>2750</td>\n",
       "      <td>178</td>\n",
       "      <td>3'55\"</td>\n",
       "      <td>7.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3800</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.8</td>\n",
       "      <td>3'55\"</td>\n",
       "      <td>41</td>\n",
       "      <td>16.1</td>\n",
       "      <td>2650</td>\n",
       "      <td>175</td>\n",
       "      <td>4'00\"</td>\n",
       "      <td>7.7</td>\n",
       "      <td>13.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3680</td>\n",
       "      <td>231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9.0</td>\n",
       "      <td>4'00\"</td>\n",
       "      <td>39</td>\n",
       "      <td>14.8</td>\n",
       "      <td>2550</td>\n",
       "      <td>172</td>\n",
       "      <td>4'05\"</td>\n",
       "      <td>7.9</td>\n",
       "      <td>12.2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3560</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9.2</td>\n",
       "      <td>4'05\"</td>\n",
       "      <td>37</td>\n",
       "      <td>13.5</td>\n",
       "      <td>2450</td>\n",
       "      <td>169</td>\n",
       "      <td>4'10\"</td>\n",
       "      <td>8.1</td>\n",
       "      <td>10.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3440</td>\n",
       "      <td>223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.4</td>\n",
       "      <td>4'10\"</td>\n",
       "      <td>35</td>\n",
       "      <td>12.2</td>\n",
       "      <td>2350</td>\n",
       "      <td>166</td>\n",
       "      <td>4'15\"</td>\n",
       "      <td>8.3</td>\n",
       "      <td>9.4</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3320</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9.6</td>\n",
       "      <td>4'15\"</td>\n",
       "      <td>33</td>\n",
       "      <td>10.9</td>\n",
       "      <td>2250</td>\n",
       "      <td>163</td>\n",
       "      <td>4'20\"</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3200</td>\n",
       "      <td>215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9.8</td>\n",
       "      <td>4'20\"</td>\n",
       "      <td>31</td>\n",
       "      <td>9.6</td>\n",
       "      <td>2150</td>\n",
       "      <td>160</td>\n",
       "      <td>4'25\"</td>\n",
       "      <td>8.7</td>\n",
       "      <td>6.6</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3080</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10.0</td>\n",
       "      <td>4'25\"</td>\n",
       "      <td>29</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2050</td>\n",
       "      <td>157</td>\n",
       "      <td>4'30\"</td>\n",
       "      <td>8.9</td>\n",
       "      <td>5.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2960</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.2</td>\n",
       "      <td>4'30\"</td>\n",
       "      <td>27</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1950</td>\n",
       "      <td>154</td>\n",
       "      <td>4'35\"</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2840</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.4</td>\n",
       "      <td>4'35\"</td>\n",
       "      <td>25</td>\n",
       "      <td>5.7</td>\n",
       "      <td>1850</td>\n",
       "      <td>151</td>\n",
       "      <td>4'40\"</td>\n",
       "      <td>9.3</td>\n",
       "      <td>2.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2720</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.6</td>\n",
       "      <td>4'40\"</td>\n",
       "      <td>23</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1750</td>\n",
       "      <td>148</td>\n",
       "      <td>4'45\"</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10.8</td>\n",
       "      <td>4'50\"</td>\n",
       "      <td>21</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1710</td>\n",
       "      <td>143</td>\n",
       "      <td>5'05\"</td>\n",
       "      <td>9.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2470</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>11.0</td>\n",
       "      <td>5'00\"</td>\n",
       "      <td>19</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1670</td>\n",
       "      <td>138</td>\n",
       "      <td>5'25\"</td>\n",
       "      <td>9.9</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2340</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11.2</td>\n",
       "      <td>5'10\"</td>\n",
       "      <td>17</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1630</td>\n",
       "      <td>133</td>\n",
       "      <td>5'45\"</td>\n",
       "      <td>10.1</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2210</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11.4</td>\n",
       "      <td>5'20\"</td>\n",
       "      <td>15</td>\n",
       "      <td>1.2</td>\n",
       "      <td>1590</td>\n",
       "      <td>128</td>\n",
       "      <td>6'05\"</td>\n",
       "      <td>10.3</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2080</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>11.6</td>\n",
       "      <td>5'30\"</td>\n",
       "      <td>13</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1550</td>\n",
       "      <td>123</td>\n",
       "      <td>6'25\"</td>\n",
       "      <td>10.5</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1950</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       女50米跑 女800米跑  女仰卧   女体前屈  女肺活量  女跳远 男1000米跑  男50米跑   男体前屈    男引体  男肺活量  \\\n",
       "分数 0   100.0    100  100  100.0   100  100     100  100.0  100.0  100.0   100   \n",
       "   1    95.0     95   95   95.0    95   95      95   95.0   95.0   95.0    95   \n",
       "   2    90.0     90   90   90.0    90   90      90   90.0   90.0   90.0    90   \n",
       "   3    85.0     85   85   85.0    85   85      85   85.0   85.0   85.0    85   \n",
       "   4    80.0     80   80   80.0    80   80      80   80.0   80.0   80.0    80   \n",
       "   5    78.0     78   78   78.0    78   78      78   78.0   78.0   78.0    78   \n",
       "   6    76.0     76   76   76.0    76   76      76   76.0   76.0   76.0    76   \n",
       "   7    74.0     74   74   74.0    74   74      74   74.0   74.0   74.0    74   \n",
       "   8    72.0     72   72   72.0    72   72      72   72.0   72.0   72.0    72   \n",
       "   9    70.0     70   70   70.0    70   70      70   70.0   70.0   70.0    70   \n",
       "   10   68.0     68   68   68.0    68   68      68   68.0   68.0   68.0    68   \n",
       "   11   66.0     66   66   66.0    66   66      66   66.0   66.0   66.0    66   \n",
       "   12   64.0     64   64   64.0    64   64      64   64.0   64.0   64.0    64   \n",
       "   13   62.0     62   62   62.0    62   62      62   62.0   62.0   62.0    62   \n",
       "   14   60.0     60   60   60.0    60   60      60   60.0   60.0   60.0    60   \n",
       "   15   50.0     50   50   50.0    50   50      50   50.0   50.0   50.0    50   \n",
       "   16   40.0     40   40   40.0    40   40      40   40.0   40.0   40.0    40   \n",
       "   17   30.0     30   30   30.0    30   30      30   30.0   30.0   30.0    30   \n",
       "   18   20.0     20   20   20.0    20   20      20   20.0   20.0   20.0    20   \n",
       "   19   10.0     10   10   10.0    10   10      10   10.0   10.0   10.0    10   \n",
       "成绩 0     7.8  3'24\"   53   24.2  3150  204   3'30\"    7.1   23.6   16.0  4540   \n",
       "   1     7.9  3'30\"   51   22.5  3100  198   3'35\"    7.2   21.5   15.0  4420   \n",
       "   2     8.0  3'36\"   49   20.8  3050  192   3'40\"    7.3   19.4   14.0  4300   \n",
       "   3     8.3  3'43\"   46   19.1  2900  185   3'47\"    7.4   17.2   13.0  4050   \n",
       "   4     8.6  3'50\"   43   17.4  2750  178   3'55\"    7.5   15.0   12.0  3800   \n",
       "   5     8.8  3'55\"   41   16.1  2650  175   4'00\"    7.7   13.6    NaN  3680   \n",
       "   6     9.0  4'00\"   39   14.8  2550  172   4'05\"    7.9   12.2   11.0  3560   \n",
       "   7     9.2  4'05\"   37   13.5  2450  169   4'10\"    8.1   10.8    NaN  3440   \n",
       "   8     9.4  4'10\"   35   12.2  2350  166   4'15\"    8.3    9.4   10.0  3320   \n",
       "   9     9.6  4'15\"   33   10.9  2250  163   4'20\"    8.5    8.0    NaN  3200   \n",
       "   10    9.8  4'20\"   31    9.6  2150  160   4'25\"    8.7    6.6    9.0  3080   \n",
       "   11   10.0  4'25\"   29    8.3  2050  157   4'30\"    8.9    5.2    NaN  2960   \n",
       "   12   10.2  4'30\"   27    7.0  1950  154   4'35\"    9.1    3.8    8.0  2840   \n",
       "   13   10.4  4'35\"   25    5.7  1850  151   4'40\"    9.3    2.4    NaN  2720   \n",
       "   14   10.6  4'40\"   23    4.4  1750  148   4'45\"    9.5    1.0    7.0  2600   \n",
       "   15   10.8  4'50\"   21    3.6  1710  143   5'05\"    9.7    0.0    6.0  2470   \n",
       "   16   11.0  5'00\"   19    2.8  1670  138   5'25\"    9.9   -1.0    5.0  2340   \n",
       "   17   11.2  5'10\"   17    2.0  1630  133   5'45\"   10.1   -2.0    4.0  2210   \n",
       "   18   11.4  5'20\"   15    1.2  1590  128   6'05\"   10.3   -3.0    3.0  2080   \n",
       "   19   11.6  5'30\"   13    0.4  1550  123   6'25\"   10.5   -4.0    2.0  1950   \n",
       "\n",
       "       男跳远  \n",
       "分数 0   100  \n",
       "   1    95  \n",
       "   2    90  \n",
       "   3    85  \n",
       "   4    80  \n",
       "   5    78  \n",
       "   6    76  \n",
       "   7    74  \n",
       "   8    72  \n",
       "   9    70  \n",
       "   10   68  \n",
       "   11   66  \n",
       "   12   64  \n",
       "   13   62  \n",
       "   14   60  \n",
       "   15   50  \n",
       "   16   40  \n",
       "   17   30  \n",
       "   18   20  \n",
       "   19   10  \n",
       "成绩 0   260  \n",
       "   1   255  \n",
       "   2   250  \n",
       "   3   243  \n",
       "   4   235  \n",
       "   5   231  \n",
       "   6   227  \n",
       "   7   223  \n",
       "   8   219  \n",
       "   9   215  \n",
       "   10  211  \n",
       "   11  207  \n",
       "   12  203  \n",
       "   13  199  \n",
       "   14  195  \n",
       "   15  190  \n",
       "   16  185  \n",
       "   17  180  \n",
       "   18  175  \n",
       "   19  170  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mark_sheet.stack(level=-1).unstack(level=0).stack(level = -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "logical-tribute",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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      ],
      "text/plain": [
       "   minutes seconds\n",
       "0        3      24\n",
       "1        3      30\n",
       "2        3      36\n",
       "3        3      43\n",
       "4        3      50\n",
       "5        3      55\n",
       "6        4      00\n",
       "7        4      05\n",
       "8        4      10\n",
       "9        4      15\n",
       "10       4      20\n",
       "11       4      25\n",
       "12       4      30\n",
       "13       4      35\n",
       "14       4      40\n",
       "15       4      50\n",
       "16       5      00\n",
       "17       5      10\n",
       "18       5      20\n",
       "19       5      30"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fuzhu1 = mark_sheet['女800米跑','成绩'].str.extract(r\"(\\d+)'(\\d+)\").rename(columns = {0:'minutes',1:'seconds'})\n",
    "fuzhu1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "numerical-nudist",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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      "text/plain": [
       "   minutes seconds\n",
       "0        3      30\n",
       "1        3      35\n",
       "2        3      40\n",
       "3        3      47\n",
       "4        3      55\n",
       "5        4      00\n",
       "6        4      05\n",
       "7        4      10\n",
       "8        4      15\n",
       "9        4      20\n",
       "10       4      25\n",
       "11       4      30\n",
       "12       4      35\n",
       "13       4      40\n",
       "14       4      45\n",
       "15       5      05\n",
       "16       5      25\n",
       "17       5      45\n",
       "18       6      05\n",
       "19       6      25"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fuzhu2 = mark_sheet['男1000米跑','成绩'].str.extract(r\"(\\d+)'(\\d+)\").rename(columns = {0:'minutes',1:'seconds'})\n",
    "fuzhu2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "attractive-latino",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20 entries, 0 to 19\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   minutes  0 non-null      float64\n",
      " 1   seconds  0 non-null      float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 448.0 bytes\n"
     ]
    }
   ],
   "source": [
    "fuzhu1['minutes'] = fuzhu1['minutes'].map(pd.to_numeric(fuzhu1['minutes']))\n",
    "fuzhu1['seconds'] = fuzhu1['seconds'].map(pd.to_numeric(fuzhu1['seconds']))\n",
    "fuzhu1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "lesser-challenge",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20 entries, 0 to 19\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   minutes  0 non-null      float64\n",
      " 1   seconds  0 non-null      float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 448.0 bytes\n"
     ]
    }
   ],
   "source": [
    "fuzhu2['minutes'] = fuzhu2['minutes'].map(pd.to_numeric(fuzhu2['minutes']))\n",
    "fuzhu2['seconds'] = fuzhu2['seconds'].map(pd.to_numeric(fuzhu2['seconds']))\n",
    "fuzhu2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "unusual-motion",
   "metadata": {},
   "outputs": [],
   "source": [
    "mark_sheet['女800米跑','成绩'] = (fuzhu1['minutes'] + fuzhu1['seconds']/60).round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "maritime-forum",
   "metadata": {},
   "outputs": [],
   "source": [
    "mark_sheet['男1000米跑','成绩'] = (fuzhu2['minutes'] + fuzhu2['seconds']/60).round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "proud-header",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20 entries, 0 to 19\n",
      "Data columns (total 24 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   (男肺活量, 成绩)     20 non-null     int64  \n",
      " 1   (男肺活量, 分数)     20 non-null     int64  \n",
      " 2   (女肺活量, 成绩)     20 non-null     int64  \n",
      " 3   (女肺活量, 分数)     20 non-null     int64  \n",
      " 4   (男50米跑, 成绩)    20 non-null     float64\n",
      " 5   (男50米跑, 分数)    20 non-null     int64  \n",
      " 6   (女50米跑, 成绩)    20 non-null     float64\n",
      " 7   (女50米跑, 分数)    20 non-null     int64  \n",
      " 8   (男体前屈, 成绩)     20 non-null     float64\n",
      " 9   (男体前屈, 分数)     20 non-null     int64  \n",
      " 10  (女体前屈, 成绩)     20 non-null     float64\n",
      " 11  (女体前屈, 分数)     20 non-null     int64  \n",
      " 12  (男跳远, 成绩)      20 non-null     int64  \n",
      " 13  (男跳远, 分数)      20 non-null     int64  \n",
      " 14  (女跳远, 成绩)      20 non-null     int64  \n",
      " 15  (女跳远, 分数)      20 non-null     int64  \n",
      " 16  (男引体, 成绩)      15 non-null     float64\n",
      " 17  (男引体, 分数)      20 non-null     int64  \n",
      " 18  (女仰卧, 成绩)      20 non-null     int64  \n",
      " 19  (女仰卧, 分数)      20 non-null     int64  \n",
      " 20  (男1000米跑, 成绩)  0 non-null      float64\n",
      " 21  (男1000米跑, 分数)  20 non-null     int64  \n",
      " 22  (女800米跑, 成绩)   0 non-null      float64\n",
      " 23  (女800米跑, 分数)   20 non-null     int64  \n",
      "dtypes: float64(7), int64(17)\n",
      "memory usage: 3.9 KB\n"
     ]
    }
   ],
   "source": [
    "mark_sheet.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "logical-japanese",
   "metadata": {},
   "source": [
    "### 其他所有数值类型的值，都要转换为float类型的值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "covered-score",
   "metadata": {},
   "outputs": [],
   "source": [
    "score_m[['男体前屈','男引体','男肺活量','BMI']] = np.array(score_m[['男体前屈','男引体','男肺活量','BMI']],dtype = float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "metallic-dollar",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 477 entries, 0 to 476\n",
      "Data columns (total 11 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   班级       477 non-null    int64  \n",
      " 1   性别       477 non-null    object \n",
      " 2   男1000米跑  451 non-null    float64\n",
      " 3   男50米跑    477 non-null    float64\n",
      " 4   男跳远      477 non-null    float64\n",
      " 5   男体前屈     477 non-null    float64\n",
      " 6   男引体      477 non-null    float64\n",
      " 7   男肺活量     477 non-null    float64\n",
      " 8   身高       477 non-null    float64\n",
      " 9   体重       477 non-null    float64\n",
      " 10  BMI      477 non-null    float64\n",
      "dtypes: float64(9), int64(1), object(1)\n",
      "memory usage: 41.1+ KB\n"
     ]
    }
   ],
   "source": [
    "score_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "anonymous-parish",
   "metadata": {},
   "outputs": [],
   "source": [
    "score_f[['女体前屈','女仰卧','女肺活量','BMI']] = np.array(score_f[['女体前屈','女仰卧','女肺活量','BMI']],dtype=float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "united-arkansas",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 593 entries, 0 to 592\n",
      "Data columns (total 11 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   班级      593 non-null    int64  \n",
      " 1   性别      593 non-null    object \n",
      " 2   女800米跑  593 non-null    float64\n",
      " 3   女50米跑   593 non-null    float64\n",
      " 4   女跳远     593 non-null    float64\n",
      " 5   女体前屈    593 non-null    float64\n",
      " 6   女仰卧     593 non-null    float64\n",
      " 7   女肺活量    593 non-null    float64\n",
      " 8   身高      593 non-null    float64\n",
      " 9   体重      593 non-null    float64\n",
      " 10  BMI     593 non-null    float64\n",
      "dtypes: float64(9), int64(1), object(1)\n",
      "memory usage: 51.1+ KB\n"
     ]
    }
   ],
   "source": [
    "score_f.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "discrete-balance",
   "metadata": {},
   "source": [
    "## 对体测成绩进行分数转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "conservative-wellington",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 这个着实没有做出来，导师给发了答案参考，还是懵懵懂懂"
   ]
  }
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